This invention relates to methods for classifying crude oils and distinguishing among crude oils by reference to the absorption spectra of the crude oils. This invention further and more particularly relates to methods of distinguishing between oil based mud filtrates and formation oil samples which are obtained by a fluid sampling borehole tool.
As seen in FIG. 1, several different interactions may occur when light strikes a sample. Typically, if the sample is fluid, some light is reflected at the boundary of the sample while the rest of the light enters the sample. Inside the sample, light is scattered by molecular excitations (Raman scattering) and by collective modes of the medium (e.g., Rayleigh scattering). In general, only a very small fraction of the light is scattered per centimeter of path by the Raman and Rayleigh scattering processes. Rather, depending upon the sample, much of the light is often absorbed. The absorption mechanisms of interest for the present invention include the electronic absorption which relates to the excitation of electronic transitions in aromatic molecules in the fluid such as asphaltenes, resins, and porphyrins; not the vibrational absorption which results from the excitation of overtones of molecular vibrations involving hydrogen atoms.
Because different fluid samples absorb energy differently, the fraction of incident light absorbed per unit of pathlength in the sample depends on the composition of the sample and the wavelength of the light. Thus, the amount of absorption as a function of the wavelength of the light, hereinafter referred to as the "absorption spectrum", has been used in the past as an indicator of the composition of the sample. For example, in U.S. Pat. No. 4,994,671 to Safinya et al., assigned to the assignee hereof, and hereby incorporated by reference herein in its entirety, it is taught, among other things, that the absorption spectrum in the wavelength range of 0.3 to 2.5 microns can be used to analyze the composition of a fluid containing oil. The disclosed technique fits a plurality of data base spectra related to a plurality of oils and to water, etc., to the obtained absorption spectrum in order to determine the amounts of different oils and water that are present in the sample.
Numerous other techniques utilizing different parts of the spectrum are known in the arts for identifying or distinguishing between oils. For example, in U.S. Pat. No. 4,620,284 to Schnell, a helium-neon laser is used to provide photons of a 0.633 micron wave length which are directed at a sample. The resulting Raman spectrum which comprises scattered light at different wavelengths than the incident light is measured, and the measured spectrum is compared with previously obtained reference spectra of a plurality of substances in order to monitor fluid flowing through an oil refinery pipeline.
In U.S. Pat. No. 4,609,821 to Summers, especially prepared rock cuttings containing at least oil from an oil-based mud are excited with ultraviolet radiation with a 0.26 micron wave length, and the frequency and intensity of the resulting excited waves (fluorescence) which are at a longer wavelength than the incident radiation are detected and measured. By comparing the fluorescent spectral profile of the detected waves with similar profiles of the oil used in the oil-based mud, a determination is made as to whether the formation oil is also found in the rock cuttings.
In U.S. Pat. No. 3,896,312 to Brown et al., which is directed specifically to finding the source of a fuel oil leak or spill, crude oil samples are obtained and are prepared in a manner such that they are of the order of 0.1 mm thick. The crude oil samples are then analyzed to find "fingerprint" valleys in the infrared spectra in the 600-1200 cm.sup.-1 (8.3 to 16.6 micron wavelength) range, and are compared against a library of reference samples so as to identify which specific oil has been found among the different types of fuel oils.
While the Schnell, Summers, and Brown et al. techniques, and many other similar techniques of the prior art may be useful in certain very limited areas, it will be appreciated that they suffer from various drawbacks For example, the use of laser equipment in Schnell severely restricts the environment in which the apparatus may be used, as lasers are not typically suited to harsh temperature and/or pressure situations such as a borehole environment. Also, the use of the Raman spectrum in Schnell imposes the requirement of equipment which can detect with very high resolution the low intensity scattered signals. The use by Summers of light having a 0.26 micron wavelength, and in Brown et al., of light in the 8.3 to 16.6 micron wavelength, severely limits the investigation of the samples to samples having nominal thickness. In fact, the Summers patent requires that the sample be diluted with solvents before investigation, while the Brown et al. patent requires that the sample be prepared to a thickness of 0.1 mm. Thus, the Summers and Brown et al. patents, do not permit an analysis of formation fluids in situ. On the other hand, while the Safinya et al. disclosure is much less limited, and has been found to be generally useful in analyzing the composition of a formation fluid either in situ or at the surface, it will be appreciated that the interpretation techniques disclosed therein are commputationally intensive. Particularly, large computing power is necessary to take a data base of spectra of numerous oils and water, and to fit those spectra to an obtained spectra in order to determine the compositional make-up of the sample. In downhole (in situ) situations, however, where the monitoring of a changing fluid flowstream in real time is desirable, and where it is less important to determine exactly the type of oil which is being obtained from the formation than it is to determine when the formation oil is being obtained as opposed to mud filtrate, it is advantageous to use less computationally intensive techniques.